1. Field of the Invention
Pricing and rating methods for property and property-related asset performance insurance products can be classified into two categories: Value-based (VB) rating and Frequency-Severity (FS) rating. In both cases insurance costs are directly related to the financial loss potentials, but the computational methods reflect the characteristics of the property or assets being insured.
VB rating generally is applied to situations where risk or loss potential can be characterized by a series of variables. For example, the loss potential and pricing for a new car may be determined by the car type, the type of loss (e.g., collision, liability, glass windshield) the amount and type of miles driven, the driving record of the insured, the geographical location and perhaps other variables. Given these variables, loss potentials have been analyzed and tables produced enabling the underwriter to look up the rates, expressed in dollars of premium/dollar of coverage, in tables. The underwriter typically multiplies the client-specific variables by the corresponding rates then adds in company-specific administrative costs to compute the overall policy premium.
For property VB insurance, some common underwriting variables are business type, building activity (e.g., hospitals, office buildings, laboratories, etc.), square footage or other attributes of size, construction attributes, fire sprinkler coverage, number of stories, location, and age. Premium rates expressed are generally categorized by these variables and together produce a premium rate. This value multiplied by the building value produces the policy premium. Actual premium values may vary by historical precedent of pricing, market demands, policy terms and conditions, contents type and property replacement values.
FS pricing is a rating and pricing method for situations where there can be large differences between insureds in the same type of industry and geographical area. In this method the probability or failure frequency (events/year) of an insurance claim or failure may be modeled or directly obtained from available data.
Engineering and underwriting risk modifiers are factors applied to the loss cost computed premium that adjust for specific customer attributes present in the current situation. For example, an engineering risk modification factor to increase the loss cost 10% could be applied for clients who have poor procedures for record-keeping and plant cleanliness. Engineering inspectors have identified a high correlation with these behaviors and customers who will have insurance claims. An underwriting risk modification factor of 10% could decrease the policy premium if high deductibles and restricted coverages are negotiated with the client. These engineering and underwriting risk modification factors make detailed premium changes based on the specific attributes of the client and the policy terms and conditions.
An example of the FS pricing method for a client is applied to an equipment breakdown premium development for a power generation station 100 shown in FIG. 1. The station has two (2) simple cycle GE 7FA turbine generators 102, 104 with two (2) transformers 106, 108 and various types of electrical switchgear and equipment (only switch 110 is shown). The first part of the premium calculation contains the frequency and severity calculation which determines the loss cost component of the premium. There are risk modification factors that customize the loss cost component for the specific client being analyzed. These factors can increase or decrease the credit and debit percentage that allows underwriting to modify the loss cost to reflect the subjective attributes (e.g., engineering factors) of the client, for example, housekeeping, recordkeeping, reliability planning, the number of equipment spares available and underwriting factors such as the deductible value selected.
The next part of the premium calculation determines the client-specific expenses, costs and profit. Another component of the premium calculation, the Excess Loss Potential refers to a loss cost premium component that accounts for the very low frequency, but very high severity loss events that are appropriate for the client. Examples of such loss events include five hundred (500) year recurrence period earthquakes, tsunamis and hurricanes. The loss event severities may be determined by specialized catastrophic modeling software. A portion of the insurance company's total loss potential may be allocated to each client as the Excess Loss Potential component of the premium.
The client may also be subjected to engineering inspections associated with jurisdictional requirements of the state or other governmental bodies. The underwriting process also includes certain client-specific costs associated with meetings, travel and the like.
Expenses considered in the underwriting process can also include costs for re-insurance and are usually added when the underwriter buys facultative re-insurance—re-insurance on a specific account. Although other expenses that involve a pro-ration of portfolio, line of business, department, or division expenses to the account level may also be added. Other premium costs are typically taxes, commissions to brokers, profit margin and other specified premium cost adders in the company's underwriting guidelines.
The FS pricing for the example above is shown below for constructing an equipment breakdown insurance price for a simple cycle gas turbine generation facility:
AnnualFailurePremiumEquipmentFrequencySeverity(Loss Costs)2 GE 7FA turbines0.025$80,000,000$2,000,0002 Transformers0.015$4,000,000$60,000Switchgear + Electrical0.030$1,000,000$30,000Total Loss Costs:$2,090,000Engineering/Underwriting Modifier (+20%-15%) [−10%]$1,881,000Excess Loss Potential:$100,000Engineering Expenses$25,000Underwriting Expenses$10,000Allocated Expenses$300,000Taxes, Commissions$30,000Profit (5%)$115,000Total Policy Premium:$2,461,000
Policy rating and pricing applied to property-related insurance pricing generally is a combination of applying the VB and FS methods. The insured's (client) property often contains a mix of highly specific equipment and other activities that are common to many similar types of locations. A client's power generation company may own a small number of highly specialized power generation locations that are rated and priced using FS but also has several branch offices where the premium may be computed by the VB method.
2. Brief Summary of the Invention
The present invention referred to herein as the insurance product, rating system and method generally relates to a rating and pricing system for quantifying the risk that the annual savings will not fall below specified levels associated with implementing and maintaining economic improvements. The invention typically involves a unique combination of qualitative and quantitative functions and factors combined in a novel fashion to develop premium costs for risk transfer associated with insuring a minimum savings amount annually or in aggregate over a multi-year policy term.
Insurance pricing systems where there may be a large amount of exposure and loss data available use standard statistical and probabilistic methods. Policies are often standardized in format and simplified to the point where underwriters construct premiums from tables where the risk attributes such as insured's age, car type, location, or building values are the key elements used to lookup the appropriate rates. Other insurance policies, such as for property insurance, may include a premium component developed from catastrophe models which estimate losses from earthquakes, for example.
Insurance pricing systems are normally designed for products which are marketed to a large number of customers usually on an annual basis, each with a relatively small loss potential. The present invention comprises an insurance product rating and pricing system designed for a relatively small number of insureds annually or over a multi-year term with each insured having a relatively large exposure. This situation cannot rely on the Law of Large Numbers principle of statistics but applies as much knowledge and actual performance data as possible into the development of the risk analysis and subsequently the premium development.
The insurance policy rating and pricing system according to the present invention may generally be based on a risk analysis where actual performance data, technical uncertainties, and other factors are combined to form input information for the pricing system. The input files, called annual aggregate risk distributions, quantify the net performance risk of all initiatives for achieving the net annual savings for each year of the policy period. For example, an improvement program may consist of work force reassignments, process re-designs, installation of advanced process controls, and energy efficiency capital projects. However, this invention is not so limited. As a further example, it also applies to other methods capable of quantifying the total net annual savings risk of potentially several hundred initiatives. These risk distributions quantify the probability of exceeding a given net annual savings value and serve as the fundamental input files, data, or equations according to the present invention. The present invention enables underwriters to apply similar procedures they would perform in standard insurance situations even though the nature of the insured risk is unique.
According to the present invention, “Savings” can be tangible or intangible and include but are not limited to increased revenue; reduced operational expenses maintenance expenses and capital expenditures; increased production through-put; reduced energy consumption; reduced emissions; increased emission credits; etc. These savings will produce additional benefits to the client in the form of enhanced creditworthiness and resulting increased availability of financing and reduced cost of financing. One skilled in the art will recognize that the present invention can generate other savings and benefits not articulated in the lists above.
The aggregate risk distributions are defined for each location on a similar basis as that applied to develop property insurance. Underwriting may be first performed at a location level and then viewed at the client level. One novel part of this invention is to enable the underwriter to develop pricing at either level. At the location level, the aggregate risk distributions are formed for the subset of all initiatives designed to be implemented at the location. At the client level, the aggregation produces only one aggregate risk distribution per year or other time periods.
If location level pricing is desired, then according to the present invention, aggregate risk distributions are applied at each location and the client level premium may be equal to the summation of the location level premiums. Some premium components may appear only at the client level, such as profit, tax, and commissions, but the system and method according to the present invention contains the flexibility to include all pricing elements in either version of the application of this insurance pricing system.
While the invention is generally discussed from the perspective of either pricing a single location or pricing at a single client level, a multi-client pricing system is also within the scope of the present invention. Multi-client as used herein includes but is not limited to an investor(s) in one or more facilities, for example power, refining, chemical, manufacturing facilities, etc. in any permutation or combination of ownership and/or geography.